import gradio as gr
import os
from utils.chatbot_logic import create_chatbot_chain

# Initialize the chatbot chain
chatbot_chain = create_chatbot_chain()

def chat_interface(message, history):
    """
    Process user message and return chatbot response
    """
    try:
        response = chatbot_chain.invoke({"input": message})
        return response["output"]
    except Exception as e:
        return f"Error: {str(e)}"

# Create Gradio Chat Interface
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown(
        """
        # 🤖 LangChain Runnables Chatbot
        
        A modular chatbot built using **LangChain Runnables** with multiple response strategies.
        
        **Features:**
        - Fact retrieval
        - Joke generation
        - Conversational memory
        - Modular and extensible design
        """
    )
    
    chatbot = gr.Chatbot(
        label="Chat History",
        height=400,
        type="messages"
    )
    
    msg = gr.Textbox(
        label="Your Message",
        placeholder="Ask me anything...",
        lines=2
    )
    
    clear = gr.Button("Clear Chat")
    
    def respond(message, chat_history):
        bot_message = chat_interface(message, chat_history)
        chat_history.append({"role": "user", "content": message})
        chat_history.append({"role": "assistant", "content": bot_message})
        return "", chat_history
    
    msg.submit(respond, [msg, chatbot], [msg, chatbot])
    clear.click(lambda: None, None, chatbot, queue=False)

if __name__ == "__main__":
    demo.launch()